Predictive performance and verification of physiologically based pharmacokinetic model of propylthiouracil.

Abstract

Background: Propylthiouracil (PTU) treats hyperthyroidism and thyroid crisis in all age groups. A variety of serious adverse effects can occur during clinical use and require attention to its pharmacokinetic and pharmacodynamic characteristics in various populations. Objective: To provide information for individualized dosing and clinical evaluation of PTU in the clinical setting by developing a physiologically based pharmacokinetic (PBPK) model, predicting ADME characteristics, and extrapolating to elderly and pediatric populations. Methods: Relevant databases and literature were retrieved to collect PTU's pharmacochemical properties and ADME parameters, etc. A PBPK model for adults was developed using PK-Sim® software to predict tissue distribution and extrapolated to elderly and pediatric populations. The mean fold error (MFE) method was used to compare the differences between predicted and observed values to assess the accuracy of the PBPK model. The model was validated using PTU pharmacokinetic data in healthy adult populations. Result: The MFE ratios of predicted to observed values of AUC0-t, Cmax, and Tmax were mainly within 0.5 and 2. PTU concentrations in various tissues are lower than venous plasma concentrations. Compared to healthy adults, the pediatric population requires quantitative adjustment to the appropriate dose to achieve the same plasma exposure levels, while the elderly do not require dose adjustments. Conclusion: The PBPK model of PTU was successfully developed, externally validated, and applied to tissue distribution prediction and special population extrapolation, which provides a reference for clinical individualized drug administration and evaluation.

• Authors: Chaozhuang Shen, Dahu Liang, Xiaohu Wang, Wenxin Shao, Kuo Geng, Xingwen Wang, Hua Sun, Haitang Xie
• Journal: Frontiers in pharmacology (Front Pharmacol) Vol. 13 Pg. 1013432 ( 2022) ISSN: 1663-9812 [Print] Switzerland
• PMID: 36278167 (Publication Type: Journal Article)
• Copyright: Copyright © 2022 Shen, Liang, Wang, Shao, Geng, Wang, Sun and Xie.